<html>
<head>
<title>
Netlab Reference Manual glmerr
</title>
</head>
<body>
<H1> glmerr
</H1>
<h2>
Purpose
</h2>
Evaluate error function for generalized linear model.

<p><h2>
Synopsis
</h2>
<PRE>
e = glmerr(net, x, t)
[e, edata, eprior] = glmerr(net, x, t)
[e, edata, eprior, y, a] = glmerr(net, x, t)
</PRE>


<p><h2>
Description
</h2>

<CODE>e = glmerr(net, x, t)</CODE> takes a generalized
linear model data structure <CODE>net</CODE> together with a matrix <CODE>x</CODE>
of input vectors and a matrix <CODE>t</CODE> of target vectors, and evaluates
the error function <CODE>e</CODE>. The choice of error function corresponds
to the output unit activation function. Each row of <CODE>x</CODE>
corresponds to one input vector and each row of <CODE>t</CODE> corresponds to
one target vector.

<p><CODE>[e, edata, eprior, y, a] = glmerr(net, x, t)</CODE> also returns
the data and prior components of the total error.

<p><CODE>[e, edata, eprior, y, a] = glmerr(net, x)</CODE> also returns a matrix <CODE>y</CODE>
giving the outputs of the models and a matrix <CODE>a</CODE> 
giving the summed inputs to each output unit, where each row
corresponds to one pattern.

<p><h2>
See Also
</h2>
<CODE><a href="glm.htm">glm</a></CODE>, <CODE><a href="glmpak.htm">glmpak</a></CODE>, <CODE><a href="glmunpak.htm">glmunpak</a></CODE>, <CODE><a href="glmfwd.htm">glmfwd</a></CODE>, <CODE><a href="glmgrad.htm">glmgrad</a></CODE>, <CODE><a href="glmtrain.htm">glmtrain</a></CODE><hr>
<b>Pages:</b>
<a href="index.htm">Index</a>
<hr>
<p>Copyright (c) Ian T Nabney (1996-9)


</body>
</html>